No abstract

Effort estimation by analogy uses information from former similar projects to predict the effort for a new project. Existing analogy-based methods are limited by their inability to handle non-quantitative data and missing values. The accuracy of predictions needs improvement as well. In this paper, we propose a new flexible method called AQUA that is able to overcome the limitations of former methods. AQUA combines ideas from two known analogy-based estimation techniques: case-based reasoning and collaborative filtering. The method is applicable to predict effort related to any object at the requirement, feature, or project levels. Which are the main contributions of AQUA when compared to other methods? First, AQUA supports non-quantitative data by defining similarity measures for different data types. Second, it is able to tolerate missing values. Third, the results from an explorative study in this paper shows that the prediction accuracy is sensitive to both the number N of analogies (similar objects) taken for adaptation and the threshold T for the degree of similarity, which is true especially for larger data sets. A fixed and small number of analogies, as assumed in existing analogy-based methods, may not produce the best accuracy of prediction. Fourth, a flexible mechanism based on learning of existing data is proposed for determining the appropriate values of N and T likely to offer the best accuracy of prediction. New criteria to measure the quality of prediction are proposed. AQUA was validated against two internal and one public domain data sets with non-quantitative attributes and missing values. The obtained results are encouraging. In addition, Empir Software Eng (2007) 12:65-106 a comparative analysis with existing analogy-based estimation methods was conducted using three publicly available data sets that were used by these methods. In two of the three cases, AQUA outperformed all other methods.

Organic–inorganic hybrid perovskites have attracted considerable attention due to their superior optoelectronic properties. Traditional one‐step solution‐processed perovskites often suffer from defects‐induced nonradiative recombination, which significantly hinders the improvement of device performance. Herein, treatment with green antisolvents for achieving high‐quality perovskite films is reported. Compared to defects‐filled ones, perovskite films by antisolvent treatment using methylamine bromide (MABr) in ethanol (MABr‐Eth) not only enhances the resultant perovskite crystallinity with large grain size, but also passivates the surface defects. In this case, the engineering of MABr‐Eth‐treated perovskites suppressing defects‐induced nonradiative recombination in perovskite solar cells (PSCs) is demonstrated. As a result, the fabricated inverted planar heterojunction device of ITO/PTAA/Cs0.15FA0.85PbI3/PC61BM/Phen‐NADPO/Ag exhibits the best power conversion efficiency of 21.53%. Furthermore, the corresponding PSCs possess a better storage and light‐soaking stability.

B e n z i m i d a z o l e s i n O n e S t e p f r o m oN i t r o a n i l i n e s a n d A l d e h y d e s

No abstract

All-inorganic CsPbI2Br, prized for its strong stability against thermal aging and light soaking, has attracted intensive attention. However, a large energy loss results from the serious energy level offset of 1.05 eV between CsPbI2Br and Spiro-MeOTAD, hindering the further efficiency improvement of perovskite solar cells. To address this issue, a moderate energy level (CsPbI2Br)1–x (CsPbI3) x layer has been introduced at the interface between CsPbI2Br and Spiro-MeOTAD to form a graded energy level alignment, the interpolation of which has offered the energy level gradient for reducing the resistance of hole transport. Correspondingly, the energy level tailoring has minimized the energy loss, and a remarkable V OC improved from 1.12 to 1.32 V, which is one of the highest values for CsPbI2Br-based solar cells. A relatively good thermal stability has also been validated. These good performances indicate that setting an intermediate energy level alignment will be a potential strategy for idealized device architecture to minimize energy loss.

Estimation by analogy (EBA) predicts effort for a new project by aggregating effort information of similar projects from a given historical data set. Existing research results have shown that a careful selection and weighting of attributes may improve the performance of the estimation methods. This paper continues along that research line and considers weighting of attributes in order to improve the estimation accuracy. More specifically, the impact of weighting (and selection) of attributes is studied as extensions to our former EBA method AQUA, which has shown promising results and also allows estimation in the case of data sets that have non-quantitative attributes and missing values. The new resulting method is called AQUA + . For attribute weighting, a qualitative analysis pre-step using rough set analysis (RSA) is performed. RSA is a proven machine learning technique for classification of objects. We exploit the RSA results in different ways and define four heuristics for attribute weighting. AQUA + was evaluated in two ways: (1) comparison between AQUA + and AQUA, along with the comparative analysis between the proposed four heuristics for AQUA + , (2) comparison of AQUA + with other EBA methods. The main evaluation results are: (1) better estimation accuracy was obtained by AQUA + compared to AQUA over all six data sets; and (2) AQUA + obtained better results than, or very close to that of other EBA methods for the three data sets applied to all the EBA methods. In conclusion, the proposed attribute weighing method using RSA can improve the estimation accuracy of EBA method AQUA + according to the empirical studies over six data sets. Testing more data sets is necessary to get results that are more statistical significant.

Photodetectors (PDs), converting incident photons into electrical signals, play a crucial role in modern optoelectronic applications such as photo detection, optical communications, and imaging. [1-7] Owing to high material quality, broad chemical tunability, long carrier diffusion lengths, and high mobility, Pb based metal halide crystalline perovskites have attracted great attention for sensitive PD applications. [8-11] Despite their striking advances, the toxicity of Pb and stability issues have severely limited their practical commercialization. [12-14] Therefore, it is highly desirable and urgent to replace Pb with other metal alternatives which are less toxic, environ